Turbo-Charge BI on Hadoop

Turbo-Charge BI on Hadoop: The Time is Now

Want to turn your Hadoop cluster into a super-powerful, analytics data warehouse? Need to run BI queries on Hadoop at top speed?

Watch this recording of a live best practice session. You'll see how leading companies are super-charging their BI on Hadoop by combining the power of Tableau with the scale of Impala, and accelerating it all with AtScale. In this session, leaders from Cloudera and Tableau share a real-world perspective on

How to get super-fast performance from BI queries on Hadoop
Deliver powerful self-service visualization directly on Hadoop
Leverage existing BI and Hadoop investments to deliver more value to more users

Trying to make Hadoop work with your BI tools (Tableau, Excel, Qlik, MicroStrategy, Pentaho...etc?). Join this interactive webinar and find out how to make it work!

In this webinar, you will learn:

- The Pitfalls of Big Data: What matters and what's a distraction OLAP on Hadoop: The best architectural options (ROLAP, MOLAP, in-memory)
- Data Warehouse Design: the benefits of schema on demand vs. schema on load

About the Speaker: Dave Mariani, CEO, AtScale

Dave Mariani ran Yahoo! data pipelines and analytics teams at the time Hadoop was born. After Yahoo!, he went on to run engineering at Klout, where he managed a 200+ node cluster and Hive Data Warehouse of over one trillion rows. He now leads AtScale Inc, helping Fortune 100 customers run their BI on Big data.

Watch this Webinar and learn how to reconcile the changing analytic needs of your business with the explosive pressures of modern big data.

Leading enterprises are taking a "BI with Big Data" approach, architecting data lakes to act as analytics data warehouses. In this session Scott Gidley, Head of Product at Zaloni is joined by Josh Klahr, Head of Product at AtScale. They share proven insights and action plans on how to define the ideal architecture for BI on Big Data.

In this session you will learn how to:

- Make data consumption-ready and take advantage of a schema-on-read approach
- Leverage data warehouse and ETL investments and skillsets for BI on Big Data
- Deliver rapid-fire access to data in Hadoop, with governance and control

At a recent online session Josh Klahr, VP of Product Management at AtScale discussed the top challenges of scaling BI on Hadoop with Nino Bice, Principal Product Manager at Microsoft, and Hal Lavendar, AVP and Chief Architect at Cognizant Technologies. Join this session as they discuss the 5 key ways to meet those challenges head-on. They'll cover how to:

- Address the top 5 challenges of scaling BI on Hadoop
- Overcome obstacles and bridge the BI and big data gap
- Achieve scale, speed and success with BI on Hadoop

When it comes to supporting BI-on-Hadoop workloads which SQL engine works best: Impala, Hive, Presto, or Spark SQL?

As Hadoop and the SQL-on-Hadoop engines mature, leading enterprises are throwing on more diverse workloads and getting highly performant results. Hadoop is no longer relegated to a platform for data science or batch processing - now companies are also pushing traditional Business Intelligence workloads to Hadoop as well.

Come learn and benefit from some surprising, and not so surprising, findings in the second edition of the largest BI-on-Hadoop Benchmark Study to date.

- Which SQL-on-Hadoop engines work best for which BI workloads
- Key considerations to help you select which engine(s) are right for your use cases
- How SQL-on-Hadoop engines continue to push performance boundaries with new innovations

How do you bridge the gap between high expectations of entrenched BI users and the rapidly changing big data landscape? Diverse data types are now mainstream in every organization and analytics are a ubiquitous enterprise priority. Many companies struggle with reconciling the investment of proven BI with the power of modern big data lakes. But the solution is more obvious than you think.

Join this session to learn from Surya Mukherjee of OVUM as he shares:

● Why the BI-Big Data gap is smaller than it seems
● How to leverage your SQL / OLAP / BI investments together with big data for immediate value
● What to do and what to avoid for success with BI on Big Data (with real-life customer stories)

As a leading site in the highly transactional online offers market, Quotient (aka Coupons.com) processes millions, and stores billions, of transactions daily. Immediate insight into what, when, and how those transactions take place is key to maintaining customer happiness and a competitive edge.

How did Quotient innovate in the face of exploding data, while enhancing the value of existing investments in BI tools and skillsets? According to Eric Sit, Quotient’s Director of BI and Data Platforms, the key was starting a BI on Hadoop evolution.

Want to turn your Hadoop cluster into a super-powerful, analytics data warehouse? Need to run BI queries on Hadoop at top speed?

Watch this recording of a live best practice session. You'll see how leading companies are super-charging their BI on Hadoop by combining the power of Tableau with the scale of Impala, and accelerating it all with AtScale. In this session, leaders from Cloudera and Tableau share a real-world perspective on

How to get super-fast performance from BI queries on Hadoop
Deliver powerful self-service visualization directly on Hadoop
Leverage existing BI and Hadoop investments to deliver more value to more users

How do you manage data and deliver insights when data volumes are exploding? Does this modern data challenge require more than a ‘traditional’ approach?

With 30 million+ members globally and hundreds of terabytes of data, Ebates' BI Team moved to a non-traditional approach as a matter of necessity. They defined what a non-traditional approach looks like and kept their Tableau business users happy.

In this recorded session, EBates BI leader, Mark Stange-Tregear, shares why and how his team successfully transitioned from traditional BI on a traditional data-warehouse, to "all in" self-service BI on Hadoop. Mark shares

Why: Why he chose to run BI on Hadoop at Ebates
How: How Ebates made the transition; the plan, challenges and end-goals
What: What he actually did, what he achieved, and lessons learned

This session features Amex's VP of Credit and Operational Risk BI, Bryan Harrison. At Amex, Bryan's BI team does risk and fraud analytics on billions of daily transactions to protect the business and its customers.

How do you give 1000's of analysts access to big data from tools they already love and use --- like Tableau and Excel --- to do critical, real-time analytics?

In this recorded session, Bryan shares best practices to achieve BI nirvana

No more data movement - Maintain data fidelity
No more pre-aggregation - Get nimble, move faster
No more build and refresh on cubes - Save time & resources

Watch this recording of a live online session, featuring Seetha Chakrapany, Director of Analytic and CRM Systems at Macy's sharing his perspective on modernizing data architecture to enable BI on Hadoop. He's joined by Dan Kogan, Director of Product Marketing for Technology Partners at Tableau, and Eric Thorsen, Vice President, Industry Solutions at Hortonworks. They share trends and insights from the BI and Hadoop sides of the equation.

In this recorded session, we also cover the critical questions and answers that BI and data infrastructure leaders will need to consider:

What are the decision triggers for a change to data architecture?

How and why do you get started with BI on Hadoop?

What questions do you need to ask related to both the business and the technology?

Yellow Pages published its first directory in 1908: it was Google before Google. It has now become an end-to-end marketing powerhouse, partnered with the largest brands in the world to connect millions of businesses to their prospects and customers.

When Richard Langlois, Yellow Pages’ Director of Enterprise Data, embarked on their Big Data journey, the team hadn’t had any experience with Hadoop. Using AtScale, Tableau, and Cloudera, the Yellow Pages team built data services for its advertisers and internal sales and marketing team.

Watch this interactive webinar to find out how to:

Go from Zero-to-Hero in months by implementing a solid Hadoop Roadmap
Enable self-service BI on Hadoop without compromising performance or security
Leverage existing skillset to deliver value to more users, faster, while maintaining control